Researchers have developed a novel data-driven method to model nonlinear flame response dynamics, which is crucial for predicting thermoacoustic instabilities in propulsion systems. This approach utilizes a dual-path temporal surrogate model trained on limited numerical data, effectively capturing the complex interplay between excitation frequency and amplitude. The framework demonstrated high accuracy in predicting single-frequency responses across various forcing conditions, with an average mean relative error of 6.69% on independent test cases. This work offers an efficient alternative for constructing nonlinear flame-response models, promising faster thermoacoustic stability analysis for combustors. AI
IMPACT Provides a more efficient method for analyzing thermoacoustic instabilities in propulsion systems, potentially speeding up design and safety assessments.
RANK_REASON Academic paper detailing a new modeling technique. [lever_c_demoted from research: ic=1 ai=1.0]
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